{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def strongly_connected_components(graph):\n",
    "    times, _ = depth_first_search(graph.nodes(), graph)\n",
    "    _, components = depth_first_search(reversed(times), graph.reverse())\n",
    "\n",
    "    return components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def depth_first_search(nodes, graph):\n",
    "    times, components, explored = [], [], set()\n",
    "\n",
    "    for node in nodes:\n",
    "        component = []\n",
    "        stack = [(False, node)]\n",
    "\n",
    "        while stack:\n",
    "            complete, i = stack.pop()\n",
    "\n",
    "            # check if already processed\n",
    "            if complete:\n",
    "                times.append(i)\n",
    "                continue\n",
    "            elif i in explored:\n",
    "                continue\n",
    "\n",
    "            # mark the node\n",
    "            component.append(i)\n",
    "            explored.add(i)\n",
    "\n",
    "            # search in depth\n",
    "            stack.append((True, i))\n",
    "            stack.extend((False, i) for i in graph[i])\n",
    "\n",
    "        if component:\n",
    "            components.append(component)\n",
    "\n",
    "    return times, components"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## graph #1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "graph = nx.DiGraph()\n",
    "graph.add_nodes_from(range(6))\n",
    "graph.add_edges_from([\n",
    "    (0, 1), (1, 2), (2, 0), \n",
    "    (3, 4), (4, 5), (5, 3),\n",
    "    (0, 5), (2, 3),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7iFVfRLRFxEnAisA6wP3F1D5rUsVAmONJH9itAflSvPWYpH7AE6QTzG7Nncdqq1gpvxVw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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d9aa668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8))\n",
    "plt.axis('off')\n",
    "nx.draw_networkx(graph, pos=nx.circular_layout(graph), node_size=400, node_color='steelblue', font_color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 2, 1], [5, 4, 3]]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strongly_connected_components(graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## graph #2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "graph = nx.DiGraph()\n",
    "graph.add_nodes_from(range(7))\n",
    "graph.add_edges_from([\n",
    "    (0, 1), (1, 2), (2, 0), \n",
    "    (0, 3), (3, 4), (4, 0),\n",
    "    (0, 5), (5, 6), (6, 0),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yM5ufAbaX9FDe9VjvRcRgYCtSJ65dgLWBmyiNjh/1VHV988i579yApMFIejgi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\nA0Ax4gwAxYgzABQjzgBQjDgDQDH/AJg2gykNKDMTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d9aaba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8))\n",
    "plt.axis('off')\n",
    "nx.draw_networkx(graph, node_size=400, node_color='steelblue', font_color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 6, 5, 4, 3, 2, 1]]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strongly_connected_components(graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## graph #3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "graph = nx.DiGraph()\n",
    "graph.add_nodes_from(range(7))\n",
    "graph.add_edges_from([\n",
    "    (0, 2), (2, 4), (4, 6), (6, 0),\n",
    "    (0, 1), (2, 3), (4, 5), (6, 7),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Pk3oWNP3YlqSPAxcC67j0cuc88zYAJH2CVHzlUCdus+qKiBnA9sAywAWSBmeI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\n3pIkNYzhLUlSw/wv4iPAyKEsxDwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110fa8390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8))\n",
    "plt.axis('off')\n",
    "nx.draw_networkx(graph, pos=nx.circular_layout(graph), node_size=400, node_color='steelblue', font_color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 6, 4, 2], [7], [5], [3], [1]]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strongly_connected_components(graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
